Publications by authors named "C R Arias"

In this work, we present a novel modeling framework for understanding the dynamics of homeostatic regulation. Inspired by engineering control theory, this framework incorporates unique features of biological systems. First, biological variables often play physiological roles, and taking this functional context into consideration is essential to fully understand the goals and constraints of homeostatic regulation.

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Background: Despite the global public health threat posed by carbapenem-resistant Enterobacter spp., clinical and molecular epidemiological studies on international isolates remain scarce. Historically, the taxonomy of Enterobacter has been challenging, limiting our understanding of the clinical characteristics and outcomes of carbapenemase-producing Enterobacter spp.

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Background: It remains unclear how high-risk Escherichia coli lineages, like sequence type (ST) 131, initially adapt to carbapenem exposure in their progression to carbapenem resistance.

Methods: Carbapenem mutation frequency was measured in multiple subclades of extended-spectrum β-lactamase (ESBL) positive ST131 clinical isolates using a fluctuation assay followed by whole genome sequencing (WGS) characterization. Genomic, transcriptomic, and porin analyses of ST131 C2/H30Rx isolate, MB1860, under prolonged, increasing carbapenem exposure was performed using two experimental evolutionary platforms to measure fast vs.

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The brain is a highly plastic organ that continually receives and integrates signals to generate functional and structural changes and homeostatic adaptations throughout life. Alterations in some signaling pathways that mediate these responses can impact brain plasticity, accelerate brain aging and potentially lead to neurodegeneration. There is substantial evidence that two important signaling pathways activated by neurotrophins, nonacronymic (VGF) and brain-derived neurotrophic factor (BDNF), are involved in substantial functions stimulating neuronal growth, differentiation, and circuit establishment during development and neuronal maintenance and plasticity in the mature brain.

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Summary: Phenotyping consists in applying algorithms to identify individuals associated with a specific, potentially complex, trait or condition, typically out of a collection of Electronic Health Records (EHRs). Because a lot of the clinical information of EHRs are lying in texts, phenotyping from text takes an important role in studies that rely on the secondary use of EHRs. However, the heterogeneity and highly specialized aspect of both the content and form of clinical texts makes this task particularly tedious, and is the source of time and cost constraints in observational studies.

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